activity
20182021
most citedSTAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL20211 cited

STAGE: Tool for Automated Extraction of Semantic Time Cues to Enrich Neural Temporal Ordering Models

Luke Breitfeller, Aakanksha Naik, Carolyn Rose

Despite achieving state-of-the-art accuracy on temporal ordering of events, neural models showcase significant gaps in performance. Our work seeks to fill one of these gaps by leve…

cs.CL2020

Adapting Event Extractors to Medical Data: Bridging the Covariate Shift

Aakanksha Naik, Jill Lehman, Carolyn Rose

We tackle the task of adapting event extractors to new domains without labeled data, by aligning the marginal distributions of source and target domains. As a testbed, we create tw…

cs.CL2020

Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation

Aakanksha Naik, Carolyn Rosé

We tackle the task of building supervised event trigger identification models which can generalize better across domains. Our work leverages the adversarial domain adaptation (ADA)…

cs.CL2019

EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference

Abhilasha Ravichander, Aakanksha Naik, Carolyn Rose +1

Quantitative reasoning is a higher-order reasoning skill that any intelligent natural language understanding system can reasonably be expected to handle. We present EQUATE (Evaluat…

cs.CL2018

Stress Test Evaluation for Natural Language Inference

Aakanksha Naik, Abhilasha Ravichander, Norman Sadeh +2

Natural language inference (NLI) is the task of determining if a natural language hypothesis can be inferred from a given premise in a justifiable manner. NLI was proposed as a ben…